Publication Type

Book Chapter

Version

submittedVersion

Publication Date

10-2020

Abstract

A systemic risk measure is proposed accounting for links and mutual dependencies between financial institutions utilizing tail event information. Financial Risk Meter (FRM) is based on least absolute shrinkage and selection operator quantile regression designed to capture tail event co-movements. The FRM focus lies on understanding active set data characteristics and the presentation of interdependencies in a network topology. Two FRM indices are presented, namely, FRM@Americas and FRM@Europe. The FRM indices detect systemic risk at selected areas and identify risk factors. In practice, FRM is applied to the return time series of selected financial institutions and macroeconomic risk factors. The authors identify companies exhibiting extreme “co-stress” as well as “activators” of stress. With the SRM@EuroArea, the authors extend to the government bond asset class, and to credit default swaps with FRM@iTraxx. FRM is a good predictor for recession probabilities, constituting the FRM-implied recession probabilities. Thereby, FRM indicates tail event behavior in a network of financial risk factors.

Keywords

Systemic Risk, Quantile Regression, Lasso, Financial Markets, Risk Management, Network Dynamics, Recession

Discipline

Finance | Finance and Financial Management

Publication

The Econometrics of Networks

Volume

42

First Page

335

Last Page

368

ISBN

9781838675769

Identifier

10.1108/S0731-905320200000042016

Publisher

Emerald

City or Country

Bingley

Embargo Period

5-19-2021

Copyright Owner and License

Authors / SKBI

Additional URL

https://doi.org/10.1108/S0731-905320200000042016

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